As attractive as self-driving cars may be, there are many industrial applications that could use greater autonomy without the expense of new equipment. Autonomous Solutions Inc. makes a hardware and software system that can be retrofitted to current vehicles to add autonomy.

At Utah State University (USU), Torrie worked on two space shuttle payloads for the National Aeronautics and Space Administration (NASA). He obtained his master’s in electrical engineering in 1999 and then managed robotics development programs for John Deere, the U.S. Department of Defense, and the U.S. Department of Energy.

Mel Torrie, founder, CEO and president of AutonomousSolutions Inc.

ASI was spun out of USU’s Center of Self-Organizing and Intelligent Systems in 2000. Torrie helped the startup raise more than $85 million under a unique business model. There is no equity, but strategic partners have exclusive rights to their vertical markets and share intellectual property (IP) ownership with ASI.

Autonomous Solutions has automated 75 types of vehicles, which it tests at its 100-acre facility in Utah. ASI’s systems have been used in the mine cleanup, a telehandler for the Los Angeles Police Department, and robotic durability testing for major automakers.

Autonomous Solutions also serves agriculture, industrial cleaning, and military applications.

This interview is available for free to Robotics Business Review readers until Jan. 31, 2018. Here’s a preview:

Pransky: What is your favorite vehicle that you have automated?

Torrie: My favorite would be the Chaos™ robot, which we designed from scratch with Legos in my basement in 1999. We then built a Styrofoam model and took it to the police force, who said they were not interested in giving us $50,000 for “that Styrofoam thing under your arm,” so I got a farmer to help.

The first version of the Chaos high-mobility robot.

We scraped it together, took it to an FBI [U.S. Federal Bureau of Investigation] show, and they paid us $1 million to build it. We sold a couple more, machined a couple of more out of aluminum, and sold them to the military. They were used for Marine exercises in Asia, but as they already had iRobot’s PackBots and Talons in Iraq and Afghanistan, they did not need any additional military mobile platforms.

However, more requests came in — and they still do on a regular basis.

Pransky: Did Chaos fuel your passion to found Autonomous Solutions?

Torrie: That was the start. What really started my path was as an undergrad in electrical engineering working on designing sound/speaker systems. I saw a wheelchair driving down the hallway by itself, so I chased it down and begged for a job. They said, “No.”

After three months, I got stuck in the elevator with the boss of the lab that created the wheelchair, and he asked if I could solder. I told him I had put soldering up on the space shuttle, and so he hired me.

ASI’s first contract was with farming OEM John Deere in 2000 to develop orchard automation.

I worked my way up in the lab, and then John Deere saw a paper that I wrote and said, “Let’s partner on robotic farming.” So for two years, I managed a John Deere program at the university and then spun out to start ASI with John Deere in 2000.

Pransky: You have a unique business model in the sense that you never had any investment capital?

Torrie: It is all been bootstrapped; we started with John Deere.

Pransky: Have you ever been tempted over the years to seek outside investment?

Torrie: Definitely in 2008, when the economy fell apart. All the corporations in mining and agriculture and construction went away in ’08, and we had to lay off and shut down other programs.

I wanted to keep my people, but investors would not talk to me at that point because no one was buying/investing in 2009 when the market crashed. Now I get contacted probably once or twice a week with investors trying to give me money.

To date, it is been all bootstrapped and no equity. Corporations have just given us money to help them innovate and develop products together. We now have separate companies for each of the market verticals: agriculture, mining, construction, cleaning, security, automotive, etc. We separate them both for liability reasons, for example, if a farmer hurts himself by disabling a safety feature, then he does not sue and hurt the mining company.

The companies are separated not only for liability, but also for equity partnering. If a company does want to secure the IP for their industry, then they can buy a minority share in one of my verticals.

We have these different companies and we have the ASI corporate which has these core building blocks. For example, the agricultural guys can now take those building blocks, and they can adapt it for farming. They can get going much faster and to market faster and not have to use, say, their own radio guy. They can leverage one that is shared across all of the vertical companies because they do not need one full-time person.

We have a company that has the hardware and software foundation, and then each of the markets develops their own application and adapts their software for their market.

Torrie: There are so many opportunities available that choosing the right ones and getting enough money to do each of them right is the greatest challenge. It is not like you have got this big blank check and now, “Go do your dream.”

It is working with partners who say, “My budget is this,” and you try to give them everything you can to fit within that budget. There are only so many people, and you can only grow so fast, so it is an exciting problem to have, but I think tons of opportunities are probably the biggest challenge.

ASI and CNH Industrial have partnered to build a concept cab-less case IH magnum and a concept New Holland T8 autonomous tractor.

Pransky: If you could wave a magic wand, what technical problem would you want solved?

Torrie: I think the biggest gap in the industries we are in, is seeing through the dust, the rain, the fog, the snowstorms and the corn crops. These weather challenges with the existing available sensors are what is holding us back from broader adoption.

The current radar technology can see through the weather, but it just does not have the fidelity or resolution, and the vehicles have to reduce their speeds or stop a lot. They have to run; it is a million dollars an hour if certain shovels and different vehicles are down in some of these industries we provide tech to.

What is needed is high-resolution radar that sees through these various weather environments at an affordable price. We do not have California sunny all the time, and we cannot field robots that can not run in a rainstorm. That would be a good technical challenge to get solved.